Cohort profile update: the Johns Hopkins HIV clinical cohort, 1989-2023.
Catherine R LeskoAnthony T FojoJeanne C KerulyY Joseph HwangOluwaseun O Falade-NwuliaLauren C ZallaLaQuita N SnowJoyce L JonesGeetanjali ChanderRichard D MoorePublished in: European journal of epidemiology (2024)
The Johns Hopkins HIV Clinical Cohort, established in 1989, links comprehensive, longitudinal clinical data for adults with HIV receiving care in the Johns Hopkins John G. Bartlett Specialty Practice in Baltimore, Maryland, USA, to aid in understanding HIV care and treatment outcomes. Data include demographics, laboratory results, inpatient and outpatient visit information and clinical diagnoses, and prescribed and dispensed medications abstracted from medical records. A subset of patients separately consents to self-report patient-centric outcomes on standardized instruments approximately every 6 months, and another subset separately consents to contribute plasma and peripheral blood mononuclear cells to a linked specimen repository approximately annually. The cohort has cumulatively enrolled over 8000 people, with just under 2000 on average attending ≥ 1 HIV primary care visit in any given year. The cohort reflects the HIV epidemic in Baltimore: in 2021, median age was 57, 64% of participants were male, 77% were non-Hispanic Black, and 37% acquired HIV through injection drug use. This update to the cohort profile of the Johns Hopkins HIV Clinical Cohort illustrates both how the population of people with HIV in Baltimore, Maryland, USA has changed over three decades, and we have adapted data collection procedures over three decades to ensure this long-running cohort remains responsive to patient characteristics and research gaps in the provision of care to people with HIV and substance use.
Keyphrases
- antiretroviral therapy
- hiv positive
- hiv infected
- hiv testing
- human immunodeficiency virus
- hiv aids
- hepatitis c virus
- men who have sex with men
- primary care
- healthcare
- palliative care
- south africa
- machine learning
- quality improvement
- newly diagnosed
- metabolic syndrome
- case report
- mental health
- chronic pain
- data analysis
- cross sectional
- deep learning
- ultrasound guided
- cancer therapy